Simulation modelling software approaches to manufacturing problems
Increased competition in many industries has resulted in a greater emphasis on developing and using advanced manufacturing systems to improve productivity and reduce costs. The complexity and dynamic behaviour of such systems, make simulation modelling one of the most popular methods to facilitate the design and assess operating strategies of these systems. The growing need for the use of simulation is reflected by a growth in the number of simulation languages and data-driven simulators in the software market. This thesis investigates which characteristics typical manufacturing simulators possess, and how the user requirements can be better fulfilled. For the purpose of software evaluation, a case study has been carried out on a real manufacturing system. Several simulation models of an automated system for electrostatic powder coating have been developed using different simulators. In addition to the evaluation of these simulators, a comprehensive evaluation framework has been developed to facilitate selection of simulation software for modelling manufacturing systems. Different hierarchies of evaluation criteria have been established for different software purposes. In particular, the criteria that have to be satisfied for users in education differ from those for users in industry. A survey has also been conducted involving a number of users of software for manufacturing simulation. The purpose of the survey was to investigate users' opinions about simulation software, and the features that they desire to be incorporated in simulation software. A methodology for simulation software selection is also derived. It consists of guidelines related to the actions to be taken and factors to be considered during the evaluation and selection of simulation software. On the basis of all the findings, proposals on how manufacturing simulators can be improved are made, both for use in education and in industry. These software improvements should result in a reduction in the amount of time and effort needed for simulation model development, and therefore make simulation more beneficial.